A likelihood used for soft decision error correction decoding is generally obtained by acquiring the minimum value of errors (Euclidean distances) between all symbol candidate points of a pattern presenting a transmitted bit of 1 and a received symbol, and the minimum value of errors between all symbol candidate points of a pattern presenting a transmitted bit of 0 and a received symbol, and converting a difference therebetween into a log likelihood ratio (LLR).
Calculation of the error (Euclidean distance) requires multiplications, and then, the minimum value needs to be selected from the plurality of candidates, resulting in an increase in a circuit scale. Further, if a circuit operating in real time is constructed, the real time property is secured by implementing likelihood generation circuits in parallel, resulting in such a problem that the number of multipliers increases as the number of parallelisms increases, which leads to an increase in the circuit scale of the likelihood generation circuit.
In contrast, for example, in Patent Literature 1, there is proposed a soft decision value generation circuit that reduces the circuit scale from the relationship of the symbol mapping by eliminating, in advance, an unnecessary calculation portion for the Euclidean distances to the symbols based on the relationship between the received signal and the mapping.